class: center, middle, inverse, title-slide .title[ # Accelerate Your Workflow: Endless Possibilities with R ] .subtitle[ ## Highlights and Examples ] .author[ ### Thomas Sharpe,
thomassharpe@isu.edu
] .date[ ### AIHEC IR Conference: July 2024 ] --- # So Many Project Ideas, Not Enough Time! -- .pull-left[ Fancy Visualizations (gganimate)  ] -- .pull-right[ Fancy Machine Learning (lots of R packages):  ] -- <b> It can be quite hard to find the time to explore and enhance </b> --- # Objective ## Scope - Demonstrate a few examples of leveraging a tool like R to speed up processes. -- - Highlight key R packages and brief overview of the code flow. -- - Spur curiosity and ideas. -- - If you think, "Hey, I can do that better, or I might tweak that a bit." That's Great! -- ## Overview - Visualization (Internal Organization) - Text File Creation (IPEDS Completions) - Excel File Creation (State Reporting or Ad Hoc Needs) - Bulk Reporting (Program Review) - Additional Examples (Reproducible Research and Analytics) - Discussion and Q&A --- # College of Southern Idaho (CSI) ## Analytics and Institutional Research (AIR) Team - FTE: 2.5 to 3.0 - Scope: Decision support, business intelligence, data-related compliance. Teamwork with IT on data governance. ## Implemented Software - Jenzabar EX ERP / SIS - Microsoft SQL Server - No Enterprise Data Warehouse - Power BI --- # Idaho State Univeristy (ISU) ## Institutional Research (IR) Team - FTE: 3.0 (soon to be 4.0!) - Scope: Decision support, business intelligence, data-related compliance, production reporting. Teamwork with IT on data governance. ## Implemented Software - Ellucian Banner - Oracle SQL - Data Warehouse (Brand New) - Tableau (Just Getting Started) -- <b> These solutions should be agnostic to the software used at most institutions </b> --- # Live Coding Session  - Visualization (Internal Organization) -- - Text File Creation (IPEDS Completions) -- - Excel File Creation (State Reporting or Ad Hoc Needs) -- - Bulk Reporting (Program Review) -- - Additional Examples (Reproducible Research and Analytics) --- # Limitations - Reporting requirement changes. - Business process changes. - Software changes. --- # Outcomes This work has allowed for... (team effort big time!!!) - Implementation of fairly wide-spread business intelligence usage -- - Promptly keeping up with new requirements (e.g. NWCCU disaggregation) <img src="data:image/png;base64,#DataAtAGlance.png" alt="IPEDS Groups" width="600px" height="250px"/> -- - Predictive analytics and implementation with stakeholders. -- - Beginning of data literacy training. -- - Improving institution-wide data documentation. --- # Conclusion  <b>https://github.com/ThomasSharpeISU/AIHEC_IR24</b> --- # Discussion and Q&A